This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The Specific Aims of this project are: 1. Measure levels of metabolites in liver and adipose tissue samples in a 500 mouse F2 intercross segregating for obesity and diabetes traits. 2. Identify metabolite quantitative trait loci (mQTL) using the data from Specific Aim #1. Our preliminary studies of metabolite QTLs indicate the presence of complex interactions that are not easily handled using traditional methods. New mQTL mapping methods will be developed and applied to efficiently and effectively localize mQTLs. 3. Combine the metabolite data and mQTL results obtained in Specific Aim #2 with clinical data to construct regulatory networks that reveal key relationships among genome regions, metabolites, and clinical traits. Methods now exist for identifying regulatory networks using gene expression and expression QTL (eQTL) data combined with related clinical traits. These approaches will be applied and extended to account for metabolites and to allow for interactions among metabolites, expression and clinical phenotypes. The improved methods will provide a powerful basis for network construction that begins with gene loci and forms a network involving mRNAs and metabolites.